What is the fundamental assumption used by the Naive Bayes classifier?

Options

  • A. Features are assumed to be conditionally independent given the class
  • B. All features must have identical values
  • C. The dataset must contain no categorical features
  • D. The classes must always have equal probability
  • E. None of the above

Correct Answer (Detailed Explanation is Below)

A. Features are assumed to be conditionally independent given the class

Detailed Explanation

Naive Bayes is a probabilistic classification algorithm based on Bayes theorem. Its name comes from the simplifying assumption that features are conditionally independent given the class. Despite this assumption, it can perform effectively in many practical classification tasks.

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